Graph Mining ? To Extract Information Using Human Interaction based on Pattern Discovery

An interaction tree pattern mining algorithms was projected to analyze tree structures and extract interaction flow patterns. In this paper, the tree based mining for human interaction flow in a discussion session is represented as a tree. Tree-based interaction mining algorithms are designed to analyze the structures of the trees and to extract interaction flow patterns. This paper deals with a mining algorithm to extract frequent patterns of human interaction explore tree mining for hidden interaction pattern discovery using classification of mining algorithms from captured content of time series of many meetings in particular time periods years ago. The paper also provides the efficient method to extract the information priority wise algorithms compare to earlier technique. The work focuses on discovering higher level knowledge about human interaction. This paper also deals to extract several interesting patterns that are useful for the interpretation of human behavior in meeting discussions, such as determining frequent interactions, typical interaction flows, and relationships between different types of interactions.